class_docstr: EfficientNet model.
code: def get_params():
      return {
          "sw": cfg.EN.STEM_W,
          "ds": cfg.EN.DEPTHS,
          "ws": cfg.EN.WIDTHS,
          "exp_rs": cfg.EN.EXP_RATIOS,
          "se_r": cfg.EN.SE_R,
          "ss": cfg.EN.STRIDES,
          "ks": cfg.EN.KERNELS,
          "hw": cfg.EN.HEAD_W,
          "nc": cfg.MODEL.NUM_CLASSES,
      }
  
imports: from pycls.core.config import cfg
  from pycls.models.blocks import activation, conv2d, conv2d_cx, drop_connect, gap2d, gap2d_cx, init_weights, linear, linear_cx, norm2d, norm2d_cx, SE
  from torch.nn import Dropout, Module
label_desc: Use image node_id 1 for calling the EffNet obj's underlying member method code with example usage: obj.get_params() and returns: dict